Marginal semiparametric transformation models for clustered multivariate competing risks data
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DOI: 10.1002/sim.9573
Abstract: Multivariate survival models are often used in studying multiple outcomes for right‐censored data. However, the outcomes of interest often have competing risks, where standard multivariate survival models may lead to invalid inferences. For example, patients… read more here.
Keywords: marginal semiparametric; risks data; multivariate competing; competing risks ... See more keywords
Penalized estimation of semiparametric transformation models with interval-censored data and application to Alzheimer’s disease
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DOI: 10.1177/0962280219884720
Abstract: Variable selection or feature extraction is fundamental to identify important risk factors from a large number of covariates and has applications in many fields. In particular, its applications in failure time data analysis have been… read more here.
Keywords: semiparametric transformation; alzheimer disease; interval censored; censored data ... See more keywords
Regression Analysis of Multivariate Current Status Data with Semiparametric Transformation Frailty Models
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DOI: 10.5705/ss.202017.0156
Abstract: This study investigates regression analysis of multivariate current status data using a class of flexible semiparametric transformation frailty models. The maximum likelihood estimation procedure is derived for the problem. In particular, a novel EM algorithm,… read more here.
Keywords: status data; regression analysis; analysis multivariate; semiparametric transformation ... See more keywords